关于应用于高对比度多尺度介质中平流-扩散的广义多尺度有限元方法的时间积分器

IF 2.1 2区 数学 Q1 MATHEMATICS, APPLIED Journal of Computational and Applied Mathematics Pub Date : 2024-11-19 DOI:10.1016/j.cam.2024.116363
Wei Xie , Juan Galvis , Yin Yang , Yunqing Huang
{"title":"关于应用于高对比度多尺度介质中平流-扩散的广义多尺度有限元方法的时间积分器","authors":"Wei Xie ,&nbsp;Juan Galvis ,&nbsp;Yin Yang ,&nbsp;Yunqing Huang","doi":"10.1016/j.cam.2024.116363","DOIUrl":null,"url":null,"abstract":"<div><div>Despite recent progress in dealing with advection–diffusion problems in high-contrast multiscale settings, there is still a need for methods that speed up calculations without compromising accuracy. In this paper, we consider the challenges of unsteady diffusion–advection problems in the presence of multiscale high-contrast media. We use the Generalized Multiscale Method (GMsFEM) as the space discretization and pay extra attention to the time solver. Traditional finite-difference methods’ accuracy and stability deteriorate in the presence of high contrast and also with an advection term. Following Contreras et al. (2023), we use exponential integrators to handle the time dependence, fully utilizing the advantages of the generalized multiscale method. For situations dominated by diffusion, our approach aligns with previous work. However, in cases where advection starts to dominate, we introduce a different local generalized eigenvalue problem to build the multiscale basis functions. This adjustment makes things more efficient since the basis functions retain more information related to the advection term. We present experiments to demonstrate the effectiveness of our proposed method.</div></div>","PeriodicalId":50226,"journal":{"name":"Journal of Computational and Applied Mathematics","volume":"460 ","pages":"Article 116363"},"PeriodicalIF":2.1000,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On time integrators for Generalized Multiscale Finite Element Methods applied to advection–diffusion in high-contrast multiscale media\",\"authors\":\"Wei Xie ,&nbsp;Juan Galvis ,&nbsp;Yin Yang ,&nbsp;Yunqing Huang\",\"doi\":\"10.1016/j.cam.2024.116363\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Despite recent progress in dealing with advection–diffusion problems in high-contrast multiscale settings, there is still a need for methods that speed up calculations without compromising accuracy. In this paper, we consider the challenges of unsteady diffusion–advection problems in the presence of multiscale high-contrast media. We use the Generalized Multiscale Method (GMsFEM) as the space discretization and pay extra attention to the time solver. Traditional finite-difference methods’ accuracy and stability deteriorate in the presence of high contrast and also with an advection term. Following Contreras et al. (2023), we use exponential integrators to handle the time dependence, fully utilizing the advantages of the generalized multiscale method. For situations dominated by diffusion, our approach aligns with previous work. However, in cases where advection starts to dominate, we introduce a different local generalized eigenvalue problem to build the multiscale basis functions. This adjustment makes things more efficient since the basis functions retain more information related to the advection term. We present experiments to demonstrate the effectiveness of our proposed method.</div></div>\",\"PeriodicalId\":50226,\"journal\":{\"name\":\"Journal of Computational and Applied Mathematics\",\"volume\":\"460 \",\"pages\":\"Article 116363\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational and Applied Mathematics\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0377042724006113\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational and Applied Mathematics","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0377042724006113","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0

摘要

尽管最近在处理高对比度多尺度环境下的平流-扩散问题方面取得了进展,但仍然需要在不影响精度的前提下加快计算速度的方法。在本文中,我们考虑了存在多尺度高对比度介质的非稳态扩散-平流问题所面临的挑战。我们使用广义多尺度法(GMsFEM)作为空间离散化方法,并对时间求解器给予了特别关注。传统有限差分法的精度和稳定性在高对比度和平流项的情况下会下降。继 Contreras 等人(2023 年)之后,我们使用指数积分器来处理时间依赖性,充分发挥了广义多尺度方法的优势。对于以扩散为主的情况,我们的方法与之前的工作一致。但是,在平流开始占主导地位的情况下,我们引入了一个不同的局部广义特征值问题来构建多尺度基础函数。由于基函数保留了更多与平流项相关的信息,因此这一调整提高了效率。我们将通过实验来证明我们提出的方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
On time integrators for Generalized Multiscale Finite Element Methods applied to advection–diffusion in high-contrast multiscale media
Despite recent progress in dealing with advection–diffusion problems in high-contrast multiscale settings, there is still a need for methods that speed up calculations without compromising accuracy. In this paper, we consider the challenges of unsteady diffusion–advection problems in the presence of multiscale high-contrast media. We use the Generalized Multiscale Method (GMsFEM) as the space discretization and pay extra attention to the time solver. Traditional finite-difference methods’ accuracy and stability deteriorate in the presence of high contrast and also with an advection term. Following Contreras et al. (2023), we use exponential integrators to handle the time dependence, fully utilizing the advantages of the generalized multiscale method. For situations dominated by diffusion, our approach aligns with previous work. However, in cases where advection starts to dominate, we introduce a different local generalized eigenvalue problem to build the multiscale basis functions. This adjustment makes things more efficient since the basis functions retain more information related to the advection term. We present experiments to demonstrate the effectiveness of our proposed method.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
5.40
自引率
4.20%
发文量
437
审稿时长
3.0 months
期刊介绍: The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.
期刊最新文献
Editorial Board Fast convergence rates and trajectory convergence of a Tikhonov regularized inertial primal–dual dynamical system with time scaling and vanishing damping Developing and analyzing a FDTD method for simulation of metasurfaces An immersed interface neural network for elliptic interface problems A stochastic Bregman golden ratio algorithm for non-Lipschitz stochastic mixed variational inequalities with application to resource share problems
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1